Significant changes in soil microbial community structure and metabolic function after Mikania micrantha invasion

Currently, Mikania micrantha (M. micrantha) has invaded Guangdong, Guangxi and other provinces in China, causing serious harm to the forests of southeastern China. Soil microorganisms play an important role in the establishment of M. micrantha invasion, affecting plant productivity, community dynamics, and ecosystem function. However, at present, how M. micrantha invasion affects soil carbon, nitrogen, and phosphorus phase functional genes and the environmental factors that cause gene expression changes remain unclear, especially in subtropical forest ecosystems. This study was conducted in Xiangtoushan National Forest Park in Guangdong Province to compare the changes in soil nutrients and microorganisms after M. micrantha invasion of a forest. The microbial community composition and metabolic function were explored by metagenome sequencing. Our results showed that after M. micrantha invasion, the soil was more suitable for the growth of gram-positive bacteria (Gemmatimonadetes). In addition, the soil microbial community structure and enzyme activity increased significantly after M. micrantha invasion. Correlation analysis and Mantel test results suggested that total phosphorus (TP), nitrate nitrogen (NO3–-N), and soil dissolved organic matter (DOM; DOC and DON), were the strong correlates of soil microbial nitrogen functional genes, while soil organic matter (SOM), soil organic carbon (SOC), total nitrogen (TN), and available phosphorus (Soil-AP) were strongly correlated with the expression of soil microbial phosphorus functional gene. Mikania micrantha invasion alters soil nutrients, microbial community composition and metabolic function in subtropical forests, creates a more favorable growth environment, and may form a positive feedback process conducive to M. micrantha invasion.

www.nature.com/scientificreports/ Three 20 m × 20 m standard sampling plots were set up under each stand, and 5 m × 5 m sampling areas were randomly arranged in each standard sample plot. Each small sample area was sampled by the "S" mixed sampling method. After the litter was removed, five topsoil cores (5 cm diameter and 10 cm in depth) were collected from random spots in each plot and combined and homogenized. At each location, three sampling plots were separated by more than 100 m. In total, 6 samples (2 treatments × 3 replications) were placed in sealed plastic bags and then immediately transported to the laboratory. The stones and roots were removed, and each fresh soil sample was ground to pass through a 2-mm mesh sieve and then divided into two subsamples. One subsample of soil was prepared to determine soil ammonium (NH 4 + -N), NO 3 --N, soil-AP, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), enzyme activities and DNA extraction. The other subsample of air-dried soil was passed through a 0.149-mm sieve to analyze the other soil properties.
Measurements of soil properties. The soil temperature was determined using a handheld thermometer (SK-250 WP, SK Stoto, Japan). The SWC was determined by oven drying for 48 h at 105 °C and calculated using the wet and dry weights. Soil pH was measured using a pH meter, in a 1:2.5 (w/v) soil-water suspension. The SOM and SOC contents were determined by the high-temperature external heat potassium dichromate oxidation volumetric method. The TN content was measured using an elemental analyzer (Elementar Vario EL III; Elementar, Germany). To determine the TP content, samples were digested with 4:1 H 2 SO 4 /HClO 4 42 , and then the supernatant was passed through a 0.45-μm glass fiber filter (Q/IEF J01-1997, Shanghai) and analyzed using a continuous-flow analytical system (Skalar San++; Skalar, the Netherlands). A 3-g air-dried soil sample was mixed with 30 mL of Mehlich-3 extracting solution, shaken immediately for 5 min, and centrifuged for 5 min at 8000 × g. The supernatant was used to determine the soil-AP content. NH 4 + -N and NO 3 --N were extracted using 2 M KCl and measured using the continuous-flow analytical system 43 . Soil MBC and MBN contents were measured using the chloroform fumigation-extraction method 44 .
Methods of DNA extraction, library preparation and metagenome sequencing. The    www.nature.com/scientificreports/ Next-generation sequencing library preparations were constructed following the manufacturer's protocol (VAHTS Universal DNA Library Prep Kit for Illumina). For each sample, 200 ng of genomic DNA was randomly fragmented to < 500 bp by sonication (Covaris S220). The fragments were treated with End Prep Enzyme Mix for end repair, 5′ phosphorylation and dA tailing in one reaction, followed by T-A ligation to add adaptors to both ends. Size selection of adaptor-ligated DNA was then performed using VAHTSTM DNA clean beads, and fragments of ~ 470 bp (with an approximate insert size of 350 bp) were recovered. Each sample was then amplified by PCR for 8 cycles using P5 and P7 primers, with both primers carrying sequences that can anneal with flow cells to perform bridge PCR and P7 primers carrying a six-base index to allow for multiplexing. The PCR products were cleaned up using VAHTSTM DNA clean beads, validated using an Agilent 2100 bioanalyzer (Agilent Technologies, Palo Alto, CA, USA), and quantified by a Qubit 3.0 fluorometer (Invitrogen, Carlsbad, CA, USA).
Then, libraries with different indices were multiplexed and loaded on an Illumina HiSe instrument according to the manufacturer's instructions (Illumina, San Diego, CA, USA). Sequencing was carried out using a 2 × 150 paired-end (PE) configuration; image analysis and base calling were conducted by HiSeq control software (HCS) + OLB + GAPipeline-1.6 (Illumina) on a HiSeq instrument.
Raw shotgun sequencing reads were trimmed using cutadapt (v1.9.1). Low-quality reads, N-rich reads and adapter-polluted reads were removed. Then, host contamination reads were removed using BWA (v0.7.12). Samples were each assembled de novo to obtain separate assemblies. Whole-genome de novo assemblies were performed using MEGAHIT (v1.13) with different k-mers. The best assembly result of Scaffold, which had the largest N50, was selected for the gene prediction analysis.
Genes of each sample were predicted using Prodigal (v3.02). CD-HIT was used to cluster genes derived from all samples with a default identity of 0.95 and coverage of 0.9. To analyze the relative abundance of unigenes in each sample, PE clean reads were mapped to unigenes using SOAPAligner (version 2.2.1) to generate read coverage information for unigenes. Gene abundance was calculated based on the number of aligned reads and normalized to gene length.
Soil enzyme assay. Enzyme analysis was conducted following the procedure outlined by Saiya-Cork et al. 46 . We investigated two important soil carbon-related hydrolases and soil nitrogen and phosphorus-related hydrolases, including β-glucosidase (βG, EC 3. . Independent sample t tests were used to compare the differences in soil properties, soil microbial enzymes, soil microbial composition and soil microbial metabolic function between the CK and M. micrantha-invaded forests. Nonmetric multidimensional scaling (NMDS) was employed to analyze soil microbial community structure 19 and microbial metabolic function based on the Bray-Curtis distance in CK and M. micrantha invasion forests. We used Euclidean distances for composition (based on relative abundances at the phylum level), functional gene expression of carbon, nitrogen and phosphorus cycling and physical and chemical properties of soil and Haversine distances for geographic data. Given these distance matrices, we computed partial Mantel correlations between composition, functional gene and physical and chemical properties of soil given geographic distance (9999 permutations) using the vegan R software package.
Soil microbial community composition and diversity.. Metagenome sequencing resulted in approximately 17 million total sequences, averaging approximately 2,797,676 per sample. Basic information on microbial sequencing data statistics after past joint and low-quality treatment is shown in Table 2. In all forests, the microbial communities were predominantly composed of the phylum Acidobacteria (ranging from 49.44 to 59.66%), followed by Proteobacteria (ranging from 24.61 to 29.22%) ( Fig. 2A). In addition, we analyzed the species at the genus level by pairwise difference comparison (Welch's t test), and the results showed that among the top 9 most abundant species, Gemmatimonadetes significantly increased after M. micrantha invasion (p < 0.05, Fig. 2B), but Actinobacteria significantly decreased (p < 0.05, Fig. 2B). Taxonomic changes indicated a shift from copiotrophic to oligotrophic groups after M. micrantha invasion.
Based on the species, we calculated the Bray-Curtis distance between the sample pairs to understand the changes in microorganisms in the taxa and used NMDS to visualize this pattern (Fig. 2C). The NMDS plots showed that there was a clear separation between the CK forest and the forest invaded by M. micrantha, indicating that the soil microbial community was largely influenced by environmental conditions. Soil microbial metabolic function. The functions of KEGG level 1 (1st tier) microorganisms were mainly divided into 6 categories, of which metabolism was the main category (ranging from 60.31 to 61.42%), www.nature.com/scientificreports/ followed by environmental information processing (ranging from 11.62 to 12.13%) (Fig. 3A). NMDS showed that there was significant separation between the CK forest and the forest invaded by M. micrantha, indicating that the invasion of M. micrantha significantly changed the soil microbial metabolic function (Fig. 3B). The function of KEGG level 2 (2nd tier) was significantly different between the two treatments according to the t test, and level 3 (3rd tier) metabolic functions were further analyzed for differences. As shown in Fig. 4A, we found that M. micrantha invasion significantly increased the metabolism of nucleotides, while the metabolism of cellular processes (cell community-prokaryotes) decreased significantly. Further analysis of significantly different metabolic functions in the 3rd tier (Fig. 4B) showed that after the invasion of M. micrantha, the monomer biosynthesis of monolactam and streptomycin increased (p < 0.05). Terpenoid backbone biosynthesis, the phosphotransferase system and glycerophospholipid metabolism (a component of the cell membrane) were also significantly increased (p < 0.05).
Changes in functional gene expression of carbon, nitrogen and phosphorus cycling. We found that βG and CBH decreased significantly after M. micrantha invasion, but NAG and AP increased significantly (Fig. 5). We also explored the microbial functions related to carbon, nitrogen and phosphorus nutrients, and the results showed that the functional genes of nitrogen and phosphorus were more easily affected by M. micrantha invasion than those of carbon (Fig. 6). After M. micrantha invasion, several nitrification bacteria (AOA, AOB and AOC) and denitrification (nosZ, nirK, norB, narG, narH and narI) and nitrogen-fixation genes (nifH, nifD and nirK) increased (p < 0.05) (Fig. 6A). The invasion of M. micrantha increased (p < 0.05) the activities of 4-phytase, ACP (class A) and ALP-phoD phosphorus-related enzymes (Fig. 6B). We counted 20 carbon-related metabolic function genes (Fig. 6C), and after a t test, we found that butanoate metabolism decreased and the pentose phosphate pathway increased after M. micrantha invasion, while other carbon metabolism pathways did not change significantly (Fig. 6D).  Table 2. Sequencing data of macrogenes of the pristine forest forests and M. micrantha-invaded forest.   www.nature.com/scientificreports/ and NO 3 --N. Thus, to identify soil physical and chemical property drivers in our data set, we correlated distancecorrected dissimilarities of community composition and functional genes with those of environmental factors (Fig. 7). Overall, soil microbial functional gene expression of nitrogen and phosphorus cycling was significantly affected by physical and chemical properties; however, there was no significant relationship between soil microbial carbon cycle functional gene expression and soil physical and chemical properties. NO 3 --N was strongly correlated with both the microbial composition (based on relative abundances at the phylum level) and soil  www.nature.com/scientificreports/ microbial nitrogen functional genes (p < 0.05). SOM, SOC, TN, and soil-AP were strongly correlated with soil microbial phosphorus functional genes (p < 0.05). There was a significant correlation between some nutrients, such as NO 3 --N, MBC, DOC and TP (p < 0.05).

Discussion
The invasion of M. micrantha significantly changed the soil microbial community structure and Actinobacteria and Gemmatimonadetes abundances. The interaction between soil microorganisms and plant invasion has attracted increasing attention 47 . Previous studies have shown that exotic plant invasion not only changes the physical and chemical properties of the soil but also affects the soil microbial community. Through metagenomic analyses, our study found that the soil microbial community structure and some microbial species changed after M. micrantha invasion (Fig. 2B,C). In the early stage, it was proven by PLFA that M. micrantha invasion can change the microbial community structure 16 . We further compared the different species (the species in the top 10 most abundant taxa after M. micrantha invasion) and found that there were significant changes in Actinobacteria and Gemmatimonadetes abundances. Carey et al. 48 obtained the same result with A. triuncialis and E. caput-medusae as invasive species, but the changes in Actinobacteria and Gemmatimonadetes abundances were not significant. Actinobacteria are gram-positive bacteria that tend to grow in barren environments 49 and have genes that encode the decomposition of cellulose and hemicellulose, which play an important role in the decomposition of carbon 50 . After M. micrantha invasion, the relative abundance of Actinobacteria decreased significantly, which affected the decomposition of SOC. Combined with carbon-related enzyme activity, we found that the SOC and MBC contents were nonsignificantly decreased but www.nature.com/scientificreports/ showed a downward trend. Gemmatimonadetes are gram-negative bacteria, and gram-negative bacteria tend to grow well under substrate-rich conditions 51 . The results showed that the substrate nutrients of M. micrantha were better after invasion, which was consistent with the significant increase in nitrogen and phosphorus nutrients, especially the contents of TP and NO 3 --N, which created an environment suitable for the growth of Gemmatimonadetes.

Soil metabolic function shift in the microbial community after invasion of M. micrantha.
As an indicator of microbial metabolism, soil enzymes play an important role in ecosystem nutrient cycling 52 . βG, CBH, NAG and AP are considered to be the main carbon-, nitrogen-and phosphorus-acquiring enzymes 53 in soil. We found that NAG and AP increased significantly after M. micrantha invasion. This result is the same as that of Li et al. 16 . The AP enzyme and CM-cellulase hydrolase increased significantly with M. micrantha invasion, increasing the mineralization rate of nitrogen and phosphorus and promoting the nitrogen and phosphorus nutrient cycle 16 . In addition to enzyme activity, the KEGG database integrates a comprehensive database of genes, enzymes, compounds and metabolic network information, which provides a more comprehensive view of the functions and utilities of microbes from both high-level and genomic perspectives 54 . We showed that the metabolic function of soil microorganisms changed significantly after M. micrantha invasion by NMDS. Similar to the results of Li et al. 17 , using CLPP, different plant communities significantly changed the catabolic capacity of microbial communities 55 . Mikania micrantha invasion increased substrate utilization activity and diversity, which greatly changed the functional composition of the soil microbial communities. We found that the invasion of M. micrantha increased the metabolism of nucleotides, weakened the metabolism of cellular community prokaryotes, and increased the biosynthesis of monobactam and streptomycin. Yin et al. 19 found that biocontrol bacteria such as Catenulispora accumulate in the rhizosphere of M. micrantha, synthesizing polyketones and antibiotics such as streptomycin to inhibit pathogenic microorganisms. We also showed that M. micrantha invasion can effectively control plant bacterial diseases from the point of view of functional metabolism and enhance the adaptation and invasion of M. micrantha to various environments to a great extent. In addition, the increase in the phosphortransfer process after M. micrantha invasion indicates that the bacteria absorb more carbohydrates after M. micrantha invasion, especially hexose, hexitol and disaccharide. www.nature.com/scientificreports/ Changes in functional gene expression of carbon, nitrogen and phosphorus cycling after the invasion of M. micrantha. The integration of microbial community structure and function into plant invasion research can provide a great deal of knowledge about the invasion process and the mechanism of microbialdriven nutrient cycling. After confirming that M. micrantha invasion alters the structure and function of microorganisms, we focused on functional genes related to carbon, nitrogen and phosphorus cycles. We found that M. micrantha invasion significantly increased nitrification, denitrification and nitrogen fixation genes (Fig. 6A). Yu et al. 36 also obtained the same results, confirming that microorganisms in the rhizosphere of chamomile can increase the content of available nitrogen. The structural equation model determined that the available nitrogen was obtained mainly through AOA-mediated nitrification, which accelerated the nitrogen cycle 36 . We found that in addition to AOA, M. micrantha invasion also significantly changed the functional abundance of AOB and AOC nitrification genes (Fig. 6A). In addition to nitrogen, other studies have shown that improving the availability of soil phosphorus is also one of the main factors for the success of plant invasion 19 . Phosphorus is a necessary nutrient element for plant growth 29 . Yin et al. 19 compared the rhizosphere microbial community between M. micrantha invasion and two native plants (Polygonum Polygonum and Paeonia lactiflora). The results showed that the enrichment of the phosphorus-solubilizing bacteria Pseudomonas and Enterobacter was helpful in increasing the available phosphorus in M. micrantha rhizosphere soil. The change in functional genes of the microbial community after M. micrantha invasion may be greater than that of species. We found that M. micrantha invasion increased phosphorus-related enzyme activity genes, such as 4-phytase, ACP (class A) and ALP-phoD, and the soil-AP content increased by 72.46% (Fig. 6B). In addition to microbial species, it was also confirmed that M. micrantha invasion could increase soil-AP content via functional metabolism.
However, M. micrantha invasion had no significant effect on SOM, and previous studies did not come to a consistent conclusion that soil carbon storage increased 8,9,[33][34][35] , decreased [57][58][59] or remained unchanged 60 after M. micrantha invasion. Our analysis of carbon-related metabolic genes showed that butyric acid metabolism decreased and pentose phosphate metabolism increased after M. micrantha invasion, while most other carbon metabolism pathways had no significant changes. Ni et al. 61 studied the relationship between carbon storage and the abundance of total PLFA microbial biomass. The results showed that the increase or decrease in soil carbon storage caused by invasion depended on microbial biomass, which had a positive impact on the growth of invasive plants 15,[62][63][64] . Our research showed that there was no significant change in MBC after M. micrantha invasion, and the carbon dynamic changes caused by M. micrantha were more dependent on the changes in carbon-related metabolic genes. Although we found differences in microbial community structure and carbon-, nitrogen-and phosphorus-related metabolic function genes, further experiments are needed to study the proteins and metabolites 65 of carbon and nutrient metabolism pathways.
Differences in microbial composition and metabolic function genes after invasion of M. micrantha and their relationships to soil properties. The invasion of exotic plants is one of the most common threats to natural ecosystems 19 . Plants invade the ecosystem to produce more litter, which can cause changes in soil conditions, such as pH value, SWC or soil nutrients [66][67][68][69][70] . Correlation analysis showed that there was a significant relationship between soil characteristics and different soil microbial compositions and metabolic functions (Figs. 7 and S1). Most studies believe that the main environmental factor driving the change in soil microbial community structure is soil pH 71,72 . In our study, NO 3 --N was strongly correlated with the microbial composition. Nitrogen is an essential element for all living organisms 73 and is involved in the formation of amino acids, nucleotides, metabolic enzymes (including nitrate reductase and the membrane lipid peroxidase defense system) and other compounds necessary for life 74  Some studies also believe that SOC and AP may be the key environmental factors affecting changes in soil microbial function 16 . In this study, it was found that SOC, AP and TN were significantly correlated with soil phosphorus functional genes (Fig. 7). TP, NO 3 --N, DOC and DON were significantly correlated with soil nitrogen functional gene (Fig. 7). In tropical forest ecosystems, there is highly weathered soil and recalcitrant P fraction formation, soil erosion, and leaching losses 76,77 . Phosphorus has become an important limiting factor in primary production and other ecological processes. For example, phosphorus plays an important role in many metabolic processes, including signal transduction, energy transfer, respiration, macromolecular biosynthesis 78 and nitrogen fixation 79 . Under the condition of phosphorus limitation, M. micrantha invasion increased the contents of AP and TP in soil (not significantly, which may be related to season), thus affecting the functional genes of soil microbial nitrogen and phosphorus. DOC and DON are the most important components of dissolved organic matter (DOM). DOM is the most active and cycling organic component and plays an important role in affecting the dynamics and interaction of nutrients and microbial functions, thereby serving as a sensitive indicator of shifts in ecological processes 80 . Some studies have shown that there is a significant positive correlation between www.nature.com/scientificreports/ DON content and NO 3 --N content. A large amount of NO 3 --N is easily reduced to NO 2 -, and reacts with SOM to form DON 81,82 . This is consistent with our results. As DOM is easily used by microorganisms, DOC and DON promote the growth of microorganisms and affect nitrogen functional genes.

Conclusions
Our study highlighted the changes in the composition and function of the microbial community after M. micrantha, such as the increase in the relative abundance of Gemmatimonadetes and the increase in streptomycin biosynthesis metabolism. Mikania micrantha significantly affects the functional metabolism of microbial nitrogen and phosphorus by mobilizing the activities of microbial enzymes related to carbon, nitrogen and phosphorus in soil and increasing nitrogen and phosphorus nutrients and DOM in soil, thus forming a positive soil-microbial relationship, which is beneficial to the growth of M. micrantha. Taken together, these results indicate that combining plant eco-physiology, microbial composition, and metabolic and soil geochemistry can provide a better mechanistic understanding and prediction of invasion feedback processes.

Data availability
All data supporting the findings of this study are available in the paper or from the corresponding author upon request.